Working paper
Environmental policy, river pollution, and infant health
Evidence from Mehta vs. Union of India
Quy-Toan Do Shareen Joshi Samuel Stolper
February 2016 Environmental Policy, River Pollution, and Infant Health:
Evidence from Mehta vs. Union of India∗
Quy-Toan Do Shareen Joshi Samuel Stolper World Bank Georgetown University Harvard University
February 19, 2016
Abstract
India’s rivers are heavily polluted. One of the more polluted sites is the city of Kanpur, on the
banks of the river Ganga (or Ganges). The river receives large amounts of toxic waste from the
city’s domestic and industrial sectors, particularly the tannery industry. We study the impact of a
landmark piece of judically mandated environmental legislation in this city. In September 1987, the
Supreme Court of India ordered the tanneries of Kanpur to either clean their waste or shut down.
We explore the mortality burden of this ruling in Kanpur district as well as districts downstream,
and find a significant drop in both river pollution (as measured by Biochemical Oxygen Demand)
and health risk (as measured by infant mortality). We also explore the channels that drive these
policy impact and cannot reject that the drop in pollution levels following the Supreme Court
decision accounted for the entire observed effect on infant mortality.
Keywords: Pollution, neonatal mortality, biochemical oxygen demand.
JEL Codes: Q53, Q56
∗We are grateful to Prashant Bharadwaj, Jishnu Das, Garance Genicot, Susan Godlonton, Rema Hanna, Hanan Jacoby, Remi Jadwab, Guido Kuersteiner, Samik Lall, Arik Levinson, Rohini Pande, Martin Rama, Martin Ravallion, John Rust, Simone Schaner, George Shambaugh, Shinsuke Tanaka, and Jennifer Tobin for useful comments. Many thanks to Mr Mehta for helpful discussions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent.
1 1 Introduction
River pollution is a growing problem. In developing countries, as much as 70 percent of industrial waste and 80 percent of domestic waste is said to flow untreated into rivers (World Water Development Report
2012). Direct exposure to untreated water is blamed for a variety of health risks: infections, chronic illnesses, reproductive issues and premature mortality of children who live on the river banks. Indirect exposure through contaminated food chains and groundwater imparts a health risk even at substantial distances from the site of pollution (World Health Organization 2008a and 2008b). In the case of rivers, pollution’s impact can be particularly severe: polluted water generally flows downward to a continuum of downstream communities, creating a trail of ecological degradation and toxicity (Oates
2001, Lipscomb and Mobarak 2007).
This paper examines these issues in the context of India, where the issue of water pollution is increasingly regarded as a crisis. According to the latest estimates, more than half of India’s rivers and other surface water bodies are now significantly polluted (CPCB 2015 as reported in Daily Mail
April 15 2015). The issue is particularly salient for the largest and holiest river, the Ganges (or
Ganga), which routinely hosts some of the largest bathing rituals in the world and has experienced a significant reduction in water flow as well as a rise in pollution levels over the past two decades.
The current Prime Minister, Narendra Modi, made the cleaning of this river a major electoral promise when he campaigned from the riverside pilgrimage city of Varanasi. Within a month of being in office, the government announced “Namami Ganga,” (Sanskrit for “Respect for the Ganges”), an Integrated
Ganges Development Project that received funding of US$334 million and promised a clean Ganges in three years. The Modi administration has recently launched the "Ganga River Basin Management Plan
— 2015", featuring a comprehensive action plan for cleaning the river in the short term (three years), medium term (five years), and long term (ten years and beyond).1 There is also strong international support for such initiatives. Since 2011, the World Bank has spent more than $1 billion on the
National Ganga River Basin Project to help the National Ganga River Basin Authority (NGRBA) build institutional capacity for cleaning the river.2
These ambitious actions, and many others across the developing world, assume that policy can be an effective tool in reducing pollution. But examples of impactful policies are hard to come by.
But much of the evidence on the impact of legislation comes from developed countries, where the major interventions were in the distant past. Alsan and Goldin (2015) for example, find that the
1The document is not released to the public, but the content was widely reported across the Indian media in the week of May 9th, 2015. The report was prepared by the IITC, a cluster of seven IITs (Bombay, Delhi, Madras, Kanpur, Kharagpur, Guwahati and Roorkee) and the plan was released at a conference in early May from the Oval Observer Foundation. Some details of the documents recommendations are summarized on the foundation’s website (http://ovalobserver.org/Event/economic-financial-instruments-restoration-ganga/), accesssed on May 12th, 2015. 2http://www.worldbank.org/en/news/feature/2015/03/23/india-the-national-ganga-river-basin-project, Accessed on May 12th, 2015.
2 establishment of water and sewage systems around Bostin can explain about 37 percent of the decline in infant mortality between 1880 and 1915. In the high pollution context of developing countries today, environmental policies are often poorly designed, feature numerous loopholes, and are loosely enforced.
Greenstone and Hanna (2014), for example, find no statistically significant impact of India’s flagship river pollution control program – the National River Conservation Plan – on surface water quality in
India.
Even when environmental policies are effective, it is often difficult to identify the specific mecha- nisms that are at work in generating the impacts. Much environmental regulation is motivated at least in part by the desire to improve public health, but when such improvements are achieved, is it be- cause of better environmental quality, or because of a change in the behavior of the target population?
Policy implementation often raises awareness of environmental problems, either explicitly through informational and educational programs or implicitly through the media and the myriad observable changes produced by the policy. Assessment of policy impacts typically measures the combined effect of environmental policy on health.
In this research, we directly target these outstanding questions about pollution policy. We study a unique and historically-important policy intervention: Supreme Court rulings sparked by the pio- neering environmental public-interest litigation in India. The lack of precedent for and quasi-random geographic incidence of these rulings - which targeted the highly-polluting tanning industry of Kan- pur, India - facilitate a difference-in-difference analysis of policy impacts. We find that the Supreme
Court verdicts produced a significant drop in both river pollution (as measured by Biochemical Oxygen
Demand) and health risk (as measured by infant mortality). This provides evidence that bottom-up regulation with local (as opposed to national) geographic scope can produce desirable environmental and health outcomes. It further contributes to a growing body of research findings on environmental policy impacts in the developing world (such as those of Galiani et al. 2004, Almond et al. 2009, and
Greenstone and Hanna 2014).
Armed with this finding, we then shift our focus to the mechanisms of policy impact. While the
Supreme Court verdict unquestionably targeted river pollution and was motivated by evidence of health concerns, the link between the two may be driven by other factors. The salience of the ruling may have improved citizen information about both pollution and health, and encouraged them to change behaviors. This is particularly an issue in the Ganga Basin, where informational campaigns were part of the policy response. Another channel is economic. Furthermore, there was significant concern about the economic impacts of regulation on an industry that was such a major source of employment and wealth in Kanpur. To shed light on the relative importance of the pollution channel - as opposed to income, behavioral, and other channels - in policy impacts, we construct two instruments for river
3 pollution. The first is upstream river pollution, which we argue is a valid instrument conditional our controls and fixed effects. The second is the Kanpur policy itself, which we do not argue to be necessarily valid because it affects pollution at the same time as it affects wages and information (among other possible determinants of health). We compare results of two separate instrumental variables (IV) regressions of infant mortality on river pollution: one in which we use only the upstream pollution instrument; and one in which we additionally use the Kanpur policy instrument. Our intuition is that the former regression captures the direct effect of river pollution on infant mortality; therefore, if the Kanpur policy’s mortality impacts came predominantly through the pollution channel, then its inclusion as a second instrument should not alter our estimates of the pollution-mortality relationship.
We propose a basic model of health that motivates a direct comparison of the coefficients generated by these two IV regressions. Because we have two potential instruments and one endogenous regressor, the Sargan-Hansen test of overidentification restrictions provides a statistical “test of mechanisms”.
We find high p-values for the Sargan-Hansen test statistic in most cases, which suggests that the
Kanpur policy did indeed reduce infant mortality primarily by reducing river pollution. This result speaks directly to a common uncertainty about whether targeting pollution reduction is valuable when informational campaigns and incentives for avoidance behavior are viable alternatives.
Our estimate of the BOD-infant mortality dose-response function represents another data point in the literature on pollution and health in developing countries. In Bangladesh, Field, Glennerster, and Hussam (2013) show that switching to wells contaminated by domestic pollution has driven infant mortality upwards. In India, Brainerd and Menon (2014) show that agricultural water pollution is associated with increases in infant mortality. Our own work shows that industrial water pollution is another contributor to infant health risk. Furthermore, our work takes the pollution spillovers literature one step forward, by connecting these spillovers to measurable health impacts for the first time.
The remainder of this paper is organized as follows. Section 2 provides an overview of the context of our study, particularly river pollution and environmental legislation in India. It also describes the specific type of environmental regulation we examine here, rulings from India’s judicial system in the aftermath of public interest litigation. Section 3 describes our model, including the key equations we seek to estimate. Section 4 describes the various sources of data. Section 5 provides empirical results from both reduced form and instrumental variable estimation strategies. Section 6 provides a discussion of the results. Section 7 concludes.
4 2 Context
2.1 Rivers and River Pollution
More than a century’s of epidemiology research has established a strong link between water pollution and human health. The early seminal work of John Snow (1854) connected the Broad Street cholera outbreak in London to fecal bacteria leaking from the sewage system. Epidemiology research (see e.g.
Fewtrell and Bartram 2001) has subsequently advanced to produce evidence linking water pollution to a host of pathogens (e.g. E. coli, rotavirus) and illnesses (cholera, diarrhea, etc.). Furthermore, drinking is not the only way to get contaminated; Cifuentes et al. (2000) identify irrigation to be a link between water pollution and health, while Carr (2001) highlights bathing, food, and person-to-person contact as modes of transmission of diseases from polluted water. More recently, the link between heightened river pollution and morbidity and mortality has been documented in both China and India. Ebenstein
(2010) finds that a one-grade deterioration in Chinese river water quality is associated with a 9.7 percent increase in the incidence of digestive cancer. Brainerd and Menon (2011), meanwhile, find that a 10-percent increase in agrichemical levels in Indian rivers during the month of conception is associated with an 11-percent increase in one-year mortality.
In addition to human and agricultural waste, industrial pollution of rivers has been the by-product of rapid economic growth and industrialization in some parts of the developing world. Small-scale factories, such as textile dyeing, pulp and paper, pharmaceuticals, leather tanning, lead battery, or metal smelting to name a few, tend to produce a large amount of waste that contains highly toxic or hazardous substances like chromium, mercury, lead, and cyanide. When untreated, these pollute rivers, streams, lakes, soil, and also groundwater resources (ILO 2011). In Shanghai for example, 3.4 million cubic metres of industrial and domestic waste pour into Suzhou creek and Huangpu river, which
flow through the heart of the city. Because of serious pollution, the river and creek have essentially become devoid of life and are blamed for high rates of cancer as well as other chronic illnesses in the surrounding area (ILO 2011).
In India, the direct health risks of poor river water quality are compounded by both the cultural importance of rivers and the country’s reliance on rivers not just for drinking water, but also for transportation and irrigation. Rivers have played a critical role in shaping India’s economy, society, culture and religion for more than 5,000 years. Seven major rivers, along with their many tributaries, provide potable water, cheap transportation, agricultural livelihoods, and spiritual anchors to India’s population of 1.3 billion people. The most significant is the Ganga, or Ganges. Worshipped as a goddess by Hindus worldwide, it flows more than 2,200 kilometers through eight Indian states. Its basin holds 47 percent of India’s irrigated land and feeds 500 million people (Hollick 2008; Government
5 of India 2009).
In the aftermath of several decades of population and industrial growth, India’s rivers are heavily polluted (United Nations 2013). The results of water quality monitoring carried out by India’s Central
Pollution Control Board (CPCB) for the indicator Biological Oxygen Demand (BOD)—which measures organic pollution (see Section 4 for further discussion)—suggests that water at approximately half of all sampling stations did not meet the threshold of acceptability for bathing (BOD below 3); the number of sampling stations exhibiting unacceptable levels of pollution (BOD above 5) has increased since
1995 (Rajaram and Das 2008; CPCB 2014). The pollution challenge has been growing over time: the number of rivers classified as “polluted” (BOD above 3) has more than doubled in the last five years, from 121 to 275, and the number of polluted river stretches, which are defined as having BOD levels in excess of 3, has also doubled from 150 in 2009 to 302 currently (CPCB, 2015, as reported in Daily
Mail, 2015). Indeed, only 160 out of nearly 8,000 towns have sewerage systems and treatment plants
(CPCB 2013). As a consequence, exposure to contaminated water can be high in the basins of rivers.
High levels of population density along the banks of the river, coupled with the ritual significance of bathing in the river, increases individuals’ exposure to river water. Two million people are said to bathe in the Ganga river each day, and 60,000 in Varanasi alone (Hamner et al. 2013). Religious festivals frequently occur on the banks of rivers. At the Kumbh Mela, which rotates between Haridwar,
Allahabad, Ujjain, and Nashik, more than 100 million people can bathe in a river within a single month
(Illiyas 2013). A growing number of studies document a relationship between pollution and health, particularly along the Ganga and its tributaries. Pandey et al. (2005) found that high concentration of nitrate, chloride and fecal coliforms in the city of Varanasi are associated with the prevalence of enteric diseases. Even in the case of treated water, improperly maintained pipes and seepage into the piped water system introduce contamination (Pandey et al. 2005). Several studies have attempted to estimate the various impacts of industrial pollution and sewage on human health, agriculture and livestock and other sectors of the economy (Shankar 2001, Dasgupta 2001, Reddy and Behera 2006).
2.2 Water Pollution Policies
The harms associated with water pollution, in India and the world over, have spawned a great many policies targeting water quality, water access, and sanitation. Researchers have, in turn, used many of these policies as natural experiments in environmental regulation. In recent years, program evaluation has linked various public health initiatives – such as water filtration and chlorination (Cutler and
Miller, 2005), piped water access (Gamper-Rabindran et al., 2010), spring protection (Kremer et al
2011), deep-water tube wells (Field et al., 2011), privatization of water provision (Galiani et al., 2005), and sanitation projects (Watson 2006, and Spears 2013) – to infant health impacts.
6 In India, there is little evidence that water quality interventions have been successful. The most salient government effort to reduce river pollution is the National River Conservation Plan (NRCP), a national, top-down program targeting domestic pollution into India’s surface waters. NRCP began in
1985 as the Ganga Action Plan but has expanded over thirty years to now cover 190 towns in 41 rivers across India. Its goal since 1987 has been to restore the Ganga River to the “Bathing Class” standard, as defined by India’s “Designated Best Use” (DBU) classification system (see Appendix Table 1 for the full rubric). The primary lever for achieving this goal has been the “interception, diversion, and treatment” of sewage (Government of India 2003); to that end, 4,704 million-liters per day of sewage treatment capacity have been created since its inception (Ministry of Environment and Forests [MoEF],
2013)3. Despite all of this, the popular media has panned NRCP for reasons such as poor inter-agency cooperation, funding imbalances across sites, and inability to keep pace with growing sewage loads
(Suresh 2007). Confirming public opinion priors, Greenstone and Hanna (2014) find no discernible impact of NRCP on water quality levels.
The executive branch, however, is not the only source of environmental regulation in India; the
Indian judiciary has, through the years, developed a reputation for environmental activism. Article
21 of the Indian Constitution provides citizens with the “Right to Life”, and much jurisprudence has centered on the protection of this constitutional right. In the famous case "Subash Kumar versus the state of Bihar", the Supreme Court invoked the Water Act of 1974 together with Article 21 of the
Constitution to rule in favor of the citizen who accused a major industrial plant of polluting the waters of the local river (Murlidhar 2006). In this judicial ruling, as well as the ruling on which we focus in this paper, the Supreme Court repeatedly stated that the Government of India has a responsibility to protect the environment.
2.3 Mehta vs. Union of India
Just as the Ganga Action Plan was ushering in ambitious interventions by the executive branch to reduce domestic river pollution, the groundwork was being laid for judicial-branch action to reduce industrial river pollution. The story of Supreme Court involvement in river pollution began in the pilgrimage city of Hardwar along the Ganga River; a matchstick tossed by a smoker resulted in the river catching on fire for more than 30 hours due to a toxic layer of chemicals produced by a pharmaceutical
firm (Mehta 2001). In response to this event, environmental lawyer and social activist M.C. Mehta
filed a writ petition in the Supreme Court of India charging that government authorities had not taken effective steps to prevent environmental pollution in the Ganga’s waters. The scale of the case, the whole 2,500-km stretch of the river, proved to be intractable. The court requested Mr. Mehta to
3Improvements to riverside bathing ghats, crematoria, toilets have also been a part of NRCP interventions (MoEF 2013)
7 narrow his focus; he chose the city of Kanpur.
Kanpur is a city of 2.9 million people lying directly on the Ganga River in Uttar Pradesh state (see
Figure 1). For more than 100 years, Kanpur has been a major center for India’s tannery industry. Most of the tanneries are located in the neighborhood of Jajmau, which lies outside the main city on the southern bank of the river Ganges. Leather is a highly polluting industry. The processes of washing, liming, fleshing, tanning, splitting and finishing involve a large number of chemicals (Cheremisinoff
2001).4 Tannery effluent is generally characterized by its strong color (reddish dull brown), high BOD, high pH, and high dissolved solids. It also contains highly toxic chemicals like sulphide and chromium.
In Jajmau, the reddish colored effluent, complete with chemicals, are routinely discharged from the tanneries directly into the river, rendering both river water and ground water unfit for drinking, irrigation, and general consumption (Beg and Ali 2008, Tewari Dubey, and Singh 2012). During the period of increased economic growth in the 1980s, pollution in Kanpur increased significantly as a result of many factors: increased diversion of the Ganga’s upstream waters to meet the growing demand for power, increased municipal waste in the city of Kanpur and increased pollution from the cluster of leather tanneries as they kept up with rising demand. Though Kanpur is relatively unique in its concentration of tanneries, the story of growing economic activity, growing demand for electricity, and growing pollution is actually common to most cities in the Ganga Basin, as well as other rivers of
India.
Mehta selected Kanpur although he was not from Kanpur and had not lived in Kanpur. “It was in the middle of the Ganga basin, the reddish color of the pollution made the pollution highly salient, and the city seemed representative of many other cities in the Ganga basin” (Mehta 2014). In his petition, Mr. Mehta named eighty-nine respondents; among them were seventy-five tanneries of the
Jajmau district of the city, the Union of India, the Chair of the Central Pollution Control Board, the
Chair of the Uttar Pradesh Pollution Control Board, and the Indian Standards Institute (Singh, G.
1995:88). The petition also claimed that the Municipal Corporation of Kanpur was not fulfilling its responsibilities. The court subsequently bifurcated the petition into two parts. The first dealt with the tanneries of Kanpur and the second with the Municipal Corporation. These are now called Mehta
I and Mehta II in legislative digests, and became the "Ganga Pollution Cases" and the most significant water pollution litigation in the Indian court system. By October 1987, the Court had invoked the
Water Act and Environment (Protection) Act as well as Article 21 of the Indian constitution to rule in Mr. Mehta’s favor and ordered the tanneries of Jajmau to clean their wastewater within six months or shut down entirely. This was followed by a January 1988 judgment that required the Kanpur local
4One ton of hide generally leads to the production of 20 to 80 m3of turbid and foul-smelling wastewater, including chromium levels of 100–400 mg/l, sulfide levels of 200–800 mg/l and high levels of fat and other solid wastes, as well as notable pathogen contamination. Pesticides are also often added for hide conservation during transport. (Cheremisinoff 2001).
8 municipal bodies to take several immediate measures to control water pollution: the relocation of
80,000 cattle housed in dairies or the safe removal of animal waste from these locations; the cleaning of the city’s sewers; the building of larger sewer systems; the construction of public latrines; and an immediate ban on the disposal of corpses into the river. The court also required all schools to devote one hour each week to environmental education and awareness.
3 Econometric Model
Our econometric model exploits the 1987 Supreme Court decision ruling in favor of Mr. Mehta. Since public interest litigation was relatively new in India at this time, and the selection of Kanpur was an arbitrary decision by Mr. Mehta when asked to reduce the scale of his original petition, we begin our analysis with the assumption of exogeneity of this ruling and rely on a reduced-form model that links pollution to infant mortality.
3.1 Reduced-form impact
To assess the impact of such ruling on welfare, we specify a simple reduced-form model of mortality:
Mortalityidt = a + bTdt + Xit · γ + eidt (1)
where Mortalityidt is a dummy variable indicating whether a child i, born in district d, in year-month t, died within the first month of life, Tdt is the policy variable – the October 1987 Mehta vs. Union of India court decision in our case – in district d and period t, and Xidt is a vector of individual, location*time characteristics, which includes location and time fixed effects. Typically, Tdt will be a dummy variable that takes value 1 in districts that are subject to environmental regulation and in periods following the date regulation was enacted. The crux of our identification strategy is that the error term eidt is such that Cov (Tdt, eidt) = 0. As discussed earlier, Mr. Mehta indicated that one key factor motivating the choice of Kanpur for his legal challenges was related to the salience of pollutants coming from the tanneries. It therefore seems that Kanpur was unlikely to have been chosen for (unobserved) characteristics that could independently affect infant mortality, reducing the concern of endogenous placement.
3.2 Mechanisms
While the reduced-form estimate of b in (1) might be of interest in itself, we further seek to gauge the relative relevance of the various channels that could lead environmental policy to affect infant mortality. To do so, we specify a parsimonious model of the determinants of infant mortality rates:
9 Mortalityidt = α + βP olldt + X˜idtγ + (Zidtδ + εidt) , (2)
where P olldt is the recorded average river pollution in district d and date t and X˜idt is a vector of observable district-time characteristics. We partition the space of unobserved risk factors into two: (i)
Zidt is an N ×1 vector of all unobserved risk factors that are also correlated with environmental policy
Tdt. These include but are not restricted to individual awareness about river water contamination, changes in factor prices stemming from the implementation of environmental policy Tdt, or any type of private or public interventions that might have been triggered by ; (ii) and by construction εidt captures the other risk factors of infant mortality and is such that Cov Tdt, εidt|X˜idt = 0.
We are interested in investigating the channels through which environmental policy Tdt reduced infant mortality rates. To do so, we put additional structure on the mechanisms and assume that Zidt responds to environmental policy according to
1 1 ˜ 1 1 Zidt = α + β Tdt + Xidtγ + εidt, (3) while pollution responds accordingly to
2 2 ˜ 2 2 P olldt = α + β Tdt + Xidtγ + εidt. (4)
Substituting both Zidt and P olldt, we can rewrite (2) so to obtain reduced-form expression:
2 1 2 1 IMRit = α + βα + α δ + ββ + β δ Tdt
˜ 2 2 2 +Xidt βγ + γ + γ1δ + βεidt + εidtδ + εidt . (5)
2 1 The total impact of environmental policy Tdt on infant mortality is given by ββ + β δ and can be decomposed into a pollution channel of magnitude ββ2, and other channels that account for a
β1δ 2 share ββ2+β1δ of the total. Contrary to β , which can be estimated from (4), Zidt is unobserved so that 1 β cannot be obtained directly. Instead, rewriting (2) by substituting for Zidt only yields
1 ˜ 1 1 1 (6) IMRit = α + α δ + βP olldt + Xidt γ + γ δ + β δ Tdt + εidtδ + εidt
1 so that we can directly estimate β and β δ by regressing Mortalityidt on Tdt and P olldt after controlling for X˜idt. However, while Tdt is argued to be orthogonal to the error term (see earlier discussion), the